About
Pramod Kumar Voola is an Engineering Manager with extensive experience in Life Sciences Clinical Trials, specializing in data engineering, automation testing, and AI. Based in New York, he has a proven track record in managing critical healthcare applications like eCOA platforms, enhancing patient safety and data accuracy. With skills in leadership, ethical AI advocacy, and mobile automation, he excels in driving innovations and managing high-performing teams. Pramod is currently pursuing a Data Science Certification from MIT and holds an AWS Cloud Practitioner credential. His career includes notable roles at Medidata Solutions, Capital One, and Cognizant Technology Solutions.
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Skills
Experience
Medidata Solution
Jul-2017 to PresentStrategic Thinking | Technical and Self Driven |
A results-oriented engineering manager with 4 years of experience leading and scaling data engineering and automation teams. Proven success in delivering impactful reporting analytics solutions and MVPs for complex products. Continuous Learner in data architecture, road-mapping, and project execution. Passionate about building high-performing teams and mentoring engineers to achieve their best work.
Core Competencies
Data Engineering: ETL pipelines, data warehousing, data modeling, Python, SQL, PySpark, AWS, Airflow
Data Science: Machine Learning Practitioner
Automation: Test automation frameworks, CI/CD pipelines
Architecture: MFE, Event Driven
Leadership: Team building, mentorship, conflict resolution, performance management
Project Management: SAFe, Agile methodologies, resource allocation, risk mitigation
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Education
Publication
Role in Research Journals
Projects
Conference/Seminar/STTP/FDP/Symposium/Workshop
InfoQ Dev Summit Boston
Conference Jul 2024
Hosted By:
InfoQ ,
Boston, Massachusetts, United StatesTwo days of actionable advice on critical dev priorities from trusted, active senior software developers.
Topics include: Generative AI, Software Supply Chain Security,
Scalable Architectures, and more.
InfoQ Dev Summit provides senior developers with the insights they need to master today's development hurdles and critical decisions. Learn from senior developers facing the same challenges as you as they share proven tactics, not just trends, empowering you to make smart, focused choices for your immediate dev roadmap.
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Applied Generative AI for Data Scientists
Workshop Jul 2024
Hosted By:
John Snow Labs ,
New York, New York, United StatesThis two-day workshop will walk you through building state-of-the-art Generative AI and Natural Language Processing (NLP) using John Snow Labs’ open-source libraries. This is a hands-on workshop for data scientists that will enable you to write and run live Python notebooks that put the technology to work.
The first day covers the open-source Spark NLP library for information extraction at scale - including reusing, training, and combining AI models for tasks like named entity recognition, text classification, spelling & grammar correction, question answering, knowledge extraction, sentiment analysis, and more. The second day focuses on libraries and integrations specifically for preparing data for RAG LLM solutions, including document splitting, cleaning, metadata enrichment, summarization, and embeddings calculation.
The workshop is organized in two four-hour-long sessions, each followed by self-guided coding, on Python notebooks relevant to each section. This is a live online workshop whose instructors are current lead contributors to the John Snow Labs open-source codebase.
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NLP Summit 2024 - Applied Generative AI and Language Processing
Workshop Sep 2024
Hosted By:
John Snow Labs ,
New York, New York, United StatesThe NLP Summit is the gathering place for those putting Generative AI, Natural Language Processing, and Large Language Models to good use. Now in its fourth year, this conference showcases best practices, real-world case studies and challenges in applying these technologies in practice – as well as the latest open-source libraries, tools, and models you can put to use today. The NLP Summit brings together the growing community interested in building Generative AI applications in healthcare, life science, finance, eCommerce, media, recruiting, and more.
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Certificates
LangChain for AI
Issued on:
Jun 2024
Issued By:
O'reilly
The holder of this badge has completed the following course by Pearson. The holder of this badge is capable of exploring different LLM APIs, understanding the LangChain framework, and building LLM applications using LangChain without requiring in-depth expertise in ML.
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Full Stack Development using Python
Issued on:
Jun 2020
Issued By:
Coding Dojo
Fundamentals of Generative AI for Beginners
Issued on:
Jul 2024
Issued By:
Amazon Web Services
Generative AI is a disruptive technology and its impact has been immense. It is causing businesses to rethink customer strategies and redesign their products, chipmakers are scrambling to keep up with the increased demand for processors, and in academia, educators are altering learning paths and curriculums in every field of study. The material presented in this course will introduce you to the world of generative AI and uncover some of the ingredients that make up this groundbreaking field. Using basic terms and a few simple examples, we will explain what generative AI is, what makes it work, and help build a foundation of knowledge that takes you to the next step on your learning journey. Throughout the course, you'll learn what large language models, neural networks, training data sets, and prompts are. You'll also become familiar with some tools and processes used to build generative AI applications.
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Generative AI with Large Language Models
Issued on:
Jul 2024
Issued By:
DeepLearning.AI
- Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment
- Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases
- Use empirical scaling laws to optimize the model's objective function across dataset size, compute budget, and inference requirements
- Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project
- Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners
Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology.
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Spark NLP for Data Scientists
Issued on:
Jul 2024
Issued By:
Udemy
This course will walk you through building state-of-the-art natural language processing (NLP) solutions using John Snow Labs’ open-source Spark NLP library. Our library consists of more than 20,000 pretrained models with 250 plus languages. This is a course for data scientists that will enable you to write and run live Python notebooks that cover the majority of the open-source library’s functionality. This includes reusing, training, and combining models for NLP tasks like named entity recognition, text classification, spelling & grammar correction, question answering, knowledge extraction, sentiment analysis and more.
The course is divided into 11 sections: Text Processing, Information Extraction, Dependency Parsing, Text Representation with Embeddings, Sentiment Analysis, Text Classification, Named Entity Recognition, Question Answering, Multilingual NLP, Advanced Topics such as Speech to text recognition, and Utility Tools &Annotators. In addition to video recordings with real code walkthroughs, we also provide sample notebooks to view and experiment. At the end of the cost, you will have an opportunity to take a certification, at no cost to you.
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Data Scientist's Toolbox
Issued on:
Dec 2021
Issued By:
Johns Hopkins University
Event:
Coursera
The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio
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Becoming an Ally to All
Issued on:
Aug 2024
Issued By: LinkedIn
Event:
Becoming an Ally to All
How Leaders Drive Results and Resolve Conflict in a Hybrid Workplace
Issued on:
Aug 2024
Issued By:
Project Management Institute
Event:
LinkedIN Learning
Becoming an effective leader in a traditional work setting can be challenging enough. Being a leader in a hybrid workplace requires an altered skill set. These leaders play many roles: Project manager, coach, mediator, productivity guru, and more to drive results. Conflict in this environment can add another layer of stress and risk to performance. In this course, Marlene Chism teaches leaders how to expand their skills to support employees and overall performance in this dynamic work environment.
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Membership
Invited Position
Honours & Awards
Doctoral and Master Thesis Guided
